@inproceedings{08e43afedd85419d970a192757cc02c4,
title = "Comparisons between an exact and a metaheuristic algorithm for the molecular distance geometry problem",
abstract = "We consider the Discretizable Molecular Distance Geometry Problem (DMDGP), which consists in a subclass of instances of the distance geometry problem related to molecular conformations for which a combinatorial reformulation can be supplied. We investigate the performances of two different algorithms for solving the DMDGP. The first one is the Branch and Prune (BP) algorithm, an exact algorithm that is strongly based on the structure of the combinatorial problem. The second one is the Monkey Search (MS) algorithm, a meta-heuristic algorithm that is inspired by the behavior of a monkey climbing trees in search for food supplies, and that exploits ideas and strategies from other meta-heuristic searches, such Genetic Algorithms, Differential Evolution, and so on. The comparison between the two algorithms is performed on a set of instances related to protein conformations. The used instances simulate data obtained from the Nuclear Magnetic Resonance (NMR), because the typical distances provided by NMR are considered and a predetermined number of wrong distances are included.",
keywords = "Branch and prune, Combinatorial optimization, Distance geometry, Monkey search, Protein molecules",
author = "Antonio Mucherino and Leo Liberti and Carlile Lavor and Nelson Maculan",
year = "2009",
month = jan,
day = "1",
doi = "10.1145/1569901.1569948",
language = "English",
isbn = "9781605583259",
series = "Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009",
publisher = "Association for Computing Machinery (ACM)",
pages = "333--340",
booktitle = "Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009",
note = "11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 ; Conference date: 08-07-2009 Through 12-07-2009",
}